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Two teacher quality measures and the role of context: evidence from Chile

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An Erratum to this article was published on 12 December 2016

Abstract

This research examines empirically the relationship between two measures of teacher quality: one based on professional standards and a second one using teacher value-added estimates. It also studies the extent to which teacher observable characteristics, such as teacher training variables, are associated to better performance on either of these measures and whether any of these two assessments is able to effectively measure teacher quality isolated from the effect of the context where teachers work. Context in this article is defined as any variable that is not under the direct control of the teacher but plays an important role on student learning and we believe is captured by school and municipal variables. The study uses hierarchical linear models and information from national and standardized assessments from Chile, specifically from the municipal education sector. Results show a small correlation between the two measures of teacher quality, in the lower end of results from previous studies conducted in the USA, and suggest that there is only a limited relationship between both measures of teacher quality. Teacher initial education type and professional development were statistically associated only to the standard-based measure of teacher quality. Context (both the school and municipal levels) plays an important role in the teacher effect measure, and in the standard-based measures, therefore, we conclude that neither of these measures are context-free. We expect that these results will contribute to the discussion about how to best measure teacher quality and how to evaluate teacher performance both in Chile and other parts of the world.

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Notes

  1. Exit exam used only with diagnostic purposes. It does not have consequences on participating students or schools, regardless of scores.

  2. Bravo, Falck, González, Manzi, and Peirano (2008) is an exception, but since the study did not control for the nested structure of the data, the validity of the results is unknown.

  3. VAR_TEACHERj included, in M3, gender, experience (log (years)), 5-year program (0/1), full-time regime (0/1), high school specialization (0/1), generic professional development offered by schools and the Ministry of Education (0/1), and other professional development and academic degree (no degree/college degree (control category)/master or PhD). VAR_SCHOOLY included urbanicity (urban = 1, rural = 0), school socioeconomic group, and the average score obtained in the tests SIMCE 2004 (M4). VAR_MUNICIPALITYz included percentage of people living in poverty, the municipality’s contribution to total education spending, the number of students enrolled at the beginning of the school year, and type of school administration.

  4. VAR_TEACHER jsm includes gender, initial education institution, type of study regime, continuing education, professional development, years of teacher experience, grade level and subject taught, expectations of maximum year of schooling teacher’s students, intention regarding future job prospects, content coverage, perception of self-efficacy teaching a subject, whether the teacher holds a teaching excellence certification (0/1), and whether he/she works in another school (0/1). Also included in VAR_TEACHER jsm are number of students’ classroom (quadratic), teacher’s classroom has a library (0/1), class parents’ mean level of education, class’ mean family income, class parents’ mean expectations about maximum education level of their child, and average class score (Math and Language).

  5. VAR_SCHOOL sm includes urbanicity (0/1), mean school socioeconomic level, school’s technology resources, school’s pedagogical resources, number of teachers holding certification of excellence in school, and average previous school score (Math and Language). VAR_MUNICIPALITY m includes percentage of people living in poverty, municipal contribution over total educational income of municipality, number of students enrolled at beginning of school year, and type of educational administration.

  6. This group is made up mostly of teachers working in the public sector.

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Acknowledgments

We thank Irma Coronado and Pilar Galleguillos for research assistance and the Ministry of Education of Chile for the data.

Author information

Authors and Affiliations

  1. Facultad de Educación, Pontificia Universidad Católica de Chile, Santiago, Chile

    Maria Veronica Santelices

  2. Vicuña Mackenna 4860, Macul, Santiago, Chile

    Maria Veronica Santelices

  3. Ontario Institute for Studies in Education, University of Toronto, 252 Bloor St W, Toronto, ON, M5S 1V6, Canada

    Edgar Valencia

  4. Facultad de Matemáticas, Departamento de Estadística, Pontificia Universidad Católica de Chile, Avda. Vicuña Mackenna 4860 - Macul, Santiago, Chile

    Jorge Gonzalez

  5. Escuela de Psicología, Centro de Medición MIDE UC, Pontificia Universidad Católica de Chile, Avda. Vicuña Mackenna 4860 - Macul, Santiago, Chile

    Sandy Taut

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  1. Maria Veronica Santelices
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Correspondence to Maria Veronica Santelices.

Ethics declarations

This research was funded by the Chilean government through the Fondecyt Grant No. 11110262, Grant Anillo SOC1107, and by Pontificia Universidad Católica de Chile through internal research funding. Although some of the authors work(ed) at the University Measurement Center in charge of the National Teacher Evaluation System (NTES), they did so as staff of the Center’s research area, which is independent and autonomous. The data had non-individual identifiers and was obtained following each institution’s data privacy protocol.

Additional information

The original version of this article was revised: Table 6 entries "Class", "School" and "Municipality" variables were incorrectly labeled under "Teacher fixed effects". Also, in the Appendix 1, table number was missing and the column headings were misplaced.

An erratum to this article is available at http://dx.doi.org/10.1007/s11092-016-9252-y.

Appendices

Appendix 1

Table 7 Descriptive statistics
Full size table

Appendix 2

Table 8 Relationship between teacher effect estimates from the Language test and different NTES instruments (Pearson correlation coefficients, n = 920)
Full size table
Table 9 Spearman’s rho correlations of teacher’s VA percentile estimates (prediction of random effect in a two-level model) across M1 to M5 for the Language test (n = 528)
Full size table

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Santelices, M.V., Valencia, E., Gonzalez, J. et al. Two teacher quality measures and the role of context: evidence from Chile. Educ Asse Eval Acc 29, 111–146 (2017). https://doi.org/10.1007/s11092-016-9247-8

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  • DOI: https://doi.org/10.1007/s11092-016-9247-8

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